Inertial Navigation System Alignment Based on Fading Kalman Filter and Fixed Point Smoother

This study concerns the divergence problem of Kalman filter (KF) in the strapdown inertial navigation system (SINS) initial alignment. Fading Kalman filter (FKF) and fixed point smoother (FPS) are investigated in this work, and an improved alignment algorithm is proposed. FKF ensures the fast convergence of filter, and the accuracy loss of FKF is compensated by FPS. A performance comparison between traditional KF alignment algorithm and the proposed algorithm demonstrates that the proposed algorithm performs better in terms of rapidity, convergence and accuracy.